Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

Many manifold learning algorithms aim to create embeddings with low or no distortion (isometric). If the data has intrinsic dimension d, it is often impossible to obtain an isometric embedding in ddimensions, but possible in s > ddimensions. Yet, most geometry preserving algorithms cannot do the latter. This paper proposes an embedding algorithm to overcome this. The algorithm accepts as input, besides the dimension d, an embedding dimension s d.

Taiwan President Lai Ching-te has cancelled a presidential trip to the African nation of Eswatini, accusing Beijing of putting pressure on its neighbours to bar his aircraft from flying over their territories. Seychelles, Mauritius and Madagascar revoked Lai's overflight permits after intense pressure and economic coercion from China, said a Taiwan official. China denied coercion, while praising the three African countries saying it had high appreciation for them. This is the first publicly known instance where a Taiwanese leader has had to cancel a foreign trip due to revoked flight permits. Eswatini, formerly known as Swaziland, is Taiwan's only diplomatic ally in Africa.

Save on iRobot products, including robot vacuums and mops designed to handle pet hair, daily messes, and hands-free cleaning with smart home integration. The brand iRobot launched the first Roomba robot vacuum back in 2002, and popularity for the handy devices skyrocketed from there. Countless competitors have emerged, but Roomba is still going strong. Its latest models have all the new features we love, from doubling as a vacuum and a mop to fantastic navigation and suction. The Roomba Max 705 is currently keeping my house clean as I test it for our robot vacuum guide, and it's doing a great job both mopping and vacuuming the floors in my massive second story.

This paper deals with price optimization, which is to find the best pricing strategy that maximizes revenue or profit, on the basis of demand forecasting models. Though recent advances in regression technologies have made it possible to reveal price-demand relationship of a large number of products, most existing price optimization methods, such as mixed integer programming formulation, cannot handle tens or hundreds of products because of their high computational costs. To cope with this problem, this paper proposes a novel approach based on network flow algorithms. We reveal a connection between supermodularity of the revenue and cross elasticity of demand. On the basis of this connection, we propose an efficient algorithm that employs network flow algorithms. The proposed algorithm can handle hundreds or thousands of products, and returns an exact optimal solution under an assumption regarding cross elasticity of demand. Even if the assumption does not hold, the proposed algorithm can efficiently find approximate solutions as good as other state-of-the-art methods, as empirical results show.

Neural Information Processing Systems http://nips.cc/